prEN ISO/IEC 5259-3
(Main)Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 3: Data quality management requirements and guidelines (ISO/IEC 5259-3:2024)
Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 3: Data quality management requirements and guidelines (ISO/IEC 5259-3:2024)
This document specifies requirements and provides guidance for establishing, implementing, maintaining and continually improving the quality of data used in the areas of analytics and machine learning.
This document does not define a detailed process, methods or metrics. Rather it defines the requirements and guidance for a quality management process along with a reference process and methods that can be tailored to meet the requirements in this document.
The requirements and recommendations set out in this document are generic and are intended to be applicable to all organizations, regardless of type, size or nature.
Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 3: Anforderungen und Leitlinien für das Datenqualitätsmanagement (ISO/IEC 5259-3:2024)
Intelligence artificielle - Qualité des données pour les analyses de données et l’apprentissage automatique - Partie 3: Exigences et lignes directrices pour la gestion de la qualité des données (ISO/IEC 5259-3:2024)
Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 3. del: Zahteve in smernice za vodenje kakovosti podatkov (ISO/IEC 5259-3:2024)
General Information
Standards Content (Sample)
SLOVENSKI STANDARD
01-april-2025
Umetna inteligenca - Kakovost podatkov za analizo in strojno učenje - 3. del:
Zahteve in smernice za vodenje kakovosti podatkov (ISO/IEC 5259-3:2024)
Artificial intelligence - Data quality for analytics and machine learning (ML) - Part 3: Data
quality management requirements and guidelines (ISO/IEC 5259-3:2024)
Künstliche Intelligenz - Datenqualität für Analytik und maschinelles Lernen (ML) - Teil 3:
Anforderungen und Leitlinien für das Datenqualitätsmanagement (ISO/IEC 5259-3:2024)
Intelligence artificielle - Qualité des données pour les analyses de données et
l’apprentissage automatique - Partie 3: Exigences et lignes directrices pour la gestion de
la qualité des données (ISO/IEC 5259-3:2024)
Ta slovenski standard je istoveten z: prEN ISO/IEC 5259-3
ICS:
35.020 Informacijska tehnika in Information technology (IT) in
tehnologija na splošno general
2003-01.Slovenski inštitut za standardizacijo. Razmnoževanje celote ali delov tega standarda ni dovoljeno.
International
Standard
ISO/IEC 5259-3
First edition
Artificial intelligence — Data
2024-07
quality for analytics and machine
learning (ML) —
Part 3:
Data quality management
requirements and guidelines
Intelligence artificielle — Qualité des données pour les analyses
de données et l’apprentissage automatique —
Partie 3: Exigences et lignes directrices pour la gestion de la
qualité des données
Reference number
ISO/IEC 5259-3:2024(en) © ISO/IEC 2024
ISO/IEC 5259-3:2024(en)
© ISO/IEC 2024
All rights reserved. Unless otherwise specified, or required in the context of its implementation, no part of this publication may
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Published in Switzerland
© ISO/IEC 2024 – All rights reserved
ii
ISO/IEC 5259-3:2024(en)
Contents Page
Foreword .v
Introduction .vi
1 Scope .1
2 Normative references .1
3 Terms and definitions .1
4 Symbols and abbreviated terms. 2
5 Intended usage . 2
6 Overall data quality management . 2
6.1 Objective.2
6.2 General .2
6.3 Requirements and recommendations .3
6.3.1 General .3
6.3.2 Data quality culture . .3
6.3.3 Management of data quality issues . .3
6.3.4 Competence management .3
6.3.5 Resource management .4
6.3.6 Management system integration .4
6.3.7 Documentation.4
6.3.8 Data quality audit and assessment.4
6.3.9 Confirmation review and data quality measures .5
6.3.10 Project-specific data quality management .5
6.4 Work products .5
7 Life cycle-specific data quality management .6
7.1 Objective.6
7.2 General .6
7.2.1 Data quality management life cycle .6
7.2.2 Data quality management life cycle stages .7
7.2.3 Project-independent tailoring of the data quality management life cycle .8
7.2.4 Horizontal aspects of the data quality management life cycle .8
7.3 Requirements and recommendations .9
7.3.1 Data motivation and conceptualization . .9
7.3.2 Data specification .9
7.3.3 Data planning .11
7.3.4 Data acquisition . . .11
7.3.5 Data preprocessing . 13
7.3.6 Data augmentation . 13
7.3.7 Data provisioning .14
7.3.8 Data decommissioning .16
7.4 Work products .17
7.4.1 Work products of data motivation and conceptualization stage .17
7.4.2 Work products of data specification stage .17
7.4.3 Work products of data planning stage .17
7.4.4 Work products of data acquisition stage .17
7.4.5 Work products of data preprocessing stage .17
7.4.6 Work products of data augmentation stage .18
7.4.7 Work products of data provisioning stage .18
7.4.8 Work products of data decommissioning stage .18
8 Horizontal processes .18
8.1 Objective.18
8.2 General .18
8.3 Requirements and recommendations .18
8.3.1 Verification and validation .18
© ISO/IEC 2024 – All rights reserved
iii
ISO/IEC 5259-3:2024(en)
8.3.2 Configuration management .19
8.3.3 Change management .19
8.3.4 Risk management . 20
8.4 Work products .21
8.4.1 Work products of verification and validation .21
8.4.2 Work products of configuration management .21
8.4.3 Work products of change management.21
8.4.4 Work products for risk management .21
9 Management of data quality in supply chains .22
9.1 Objective. 22
9.2 Requirements and recommendations . 22
9.3 Work products . 22
10 Management of data processing tools .
...
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